in the human oral mucosa
Maren Bråten Solhaug
Institute of Oral Biology Faculty of Dentistry University of Oslo, Norway
© Maren Bråten Solhaug, 2023
Series of dissertations submitted to the Faculty of Dentistry, University of Oslo
All rights reserved. No part of this publication may be
reproduced or transmitted, in any form or by any means, without permission.
Print production: Graphics Center, University of Oslo.
Table of Contents
ACKNOWLEDGEMENTS ... 5
ABBREVATIONS ... 6
INTRODUCTION ... 7
The oral mucosa ... 7
The immune system ... 8
Antigen presentation ... 9
Antigen presenting cells of the oral mucosa ... 11
Macrophages ... 11
Dendritic cells (DCs) ... 11
Langerhans cells ... 14
Oral lichen planus (OLP) ... 17
Oral tongue squamous cell carcinoma (OTSCC) ... 18
Epidemiology ... 18
Risk factors ... 19
Treatment ... 19
Prognosis ... 19
Tumor staging and –grading ... 20
The TNM system ... 20
WHO Histopathological grading ... 22
Pathogenesis of OTSCC ... 22
KLF4 in OTSCC ... 22
AIMS ... 23
METHODS ... 24
SUMMARY OF RESULTS ... 25
METHODOLOGICAL CONSIDERATIONS ... 26
Immunofluorescent and immunohistochemical staining ... 27
Quantification of cells (Papers II and III) ... 28
Flow cytometry (Papers I and II)... 28
Single cell RNA-sequencing (scRNAseq) ... 29
Gene Ontology enrichment analysis (GO-analysis) (Paper I) ... 30
OTSCC cohort and Tissue microarray (TMA) (Paper III) ... 31
DISCUSSION ... 31
Paper I... 31
Macrophages ... 32
Dendritic cells ... 33
Paper II... 34
Origin of langerin+ cells in NOM ... 34
Origin of langerin-expressing cells in oral lichen planus ... 35
LCs versus langerin+ DC2s ... 35
Paper III... 36
CONCLUSIONS AND FUTURE PERSPECTIVES ... 38
REFERENCES ... 40
ERRATA ... 54
First, I would like to thank the Faculty of Dentistry, University of Oslo for funding the PhD-program and the Institute of Oral Biology (IOB) for giving me the opportunity to carry out my PhD.
From the bottom of my heart, I would like to thank my main supervisors professor Espen Baekkevold, professor (now emeritus) Karl Schenck and my co-supervisors associate professors Tine M. Søland and Inger Johanne Schytte Blix. It has been a privilege to work under such capacities in their respective fields. Your guidance, with insightful comments and suggestions through all phases of this project is highly appreciated. I also thank you for giving me challenges, trust and space to develop myself as a researcher. I am deeply grateful for your never-ending optimism and believe in me and my project.
I would also like to express my gratitude to my co-authors:
- Olaf J. F. Schreurs, for your support, punctilious review of my manuscripts and for sharing your excellent laboratory (and gardening-) knowledge,
- Diana Domanska, for introducing me to the world of scRNA-sequencing, and your patience with my numerous (not always so clever) questions,
- Dipak Sapkota and Inger-Heidi Bjerkli, for their contribution, valuable comments and suggestions during the work with Paper II,
- Else K B Hals and Andreas Karatsaidis for providing the biopsies.
- All the patients that participated in the research project,
- All the colleagues at the IOB, the Institute of Clinical Dentistry, the Department of Pathology at Rikshospitalet, the Department of Pharmacology (RH), the Department of Rheumatology and Dermatology and Infectious Diseases, Ullevål Hospital, that have contributed with fruitful scientific discussions and for direct or indirect contributions to this work. Also parts of it that are not included in this thesis,
- Sushma Panday, Maria Balta and “The Oral Physiology and Cancer Research Group” for scientific and cheering talks and support,
- Gro and Kjersti for always being there for me, and for making me laugh even during the toughest times.
Moreover, I would like to express my sincere gratitude to professor emeritus Tore Solheim. With your sharp mind and profound knowledge in the field of pathology you have been a role model for me since I was studying for my master degree. Thank you for all the hours you have spent teaching me oral pathology diagnostics.
Finally, I would like to thank my family and friends for your contribution to a joyful life outside work.
To my boys, Håvard and Vebjørn, for your patience during the most busy periods. Your welcome-home- hugs are pure medicine. To Harald: It is claimed that the most important choice a woman can make for her carrier is her choice of husband. I know that is true. Thank you for encouraging me and for your endless faith in me during ups and downs in this project.
Oslo, 11.9.2022 Maren Bråten Solhaug
AJCC: American Joint Committee on Cancer aLCs: Activated LCs and
ALK5: TGFβ type I receptor kinase APC: Antigen presenting cell BCRs: B-cell receptor
CADM: Cell adhesion molecule
cDC: Conventional dendritic cell (type 1 or 2) CLIP: Class II-associated invariant chain peptide DAMP: Damage-associated molecular pattern DC: Dendritic cell
DEG: Differential expressed gene
DNGR1: Protein encoded by Clec9A, not abbreviation.
DOI: Depth of invasion
EGFR: Epidermal growth factor receptor ER: Endoplasmatic reticulum
FC: Flow cytometry
FFPE: Formalin-fixed, paraffin-embedded FGFR: Fibroblast growth factor receptor FMO: Fluorescent minus one
GEPIA: Gene Expression Profiling Interactive Analysis software
GLP: Genital lichen planus
GMP: The granulocyte-macrophage progenitor GO: Gene Ontology
GO-analysis: Gene Ontology enrichment analysis GVHD:
Graft versus host disease
HNSCC: Head and neck squamous cell carcinoma HPV: Human papilloma-virus
ICB: immune checkpoint blockade iDC: Inflammatory dendritic cell IDO: Indoleamine 2,3-dioxygenase 1 IL: Interleukin
ITGAM: Integrin alpha M KLF4: Krüppel-like factor 4 LC: Langerhans cell LC1: Langerhans cell type 1 LC2: Langerhans cell type 2
LMP2: Subunit of proteasome (not an abbreviation) LN: Lymph node
LYVE1: Lymphatic vessel endothelial hyaluronan receptor 1
MHC: Major histocompatibility complex mig-LCs: Migratory LCs
MIIC: MHC class II compartment;
moDC: Monocyte-derived dendritic cells
mRNA: Messenger RNA mtDNA: Mitochondrial DNA NK-cell: Natural killer cell
NLRC5: NOD-, LRR- and CARD-containing 5 NOM: Normal oral mucosa
oAPC: Oral mucosa APC oLCs: Oral mucosa LCs OLP: Oral lichen planus OLR: Oral lichenoid reactions oMF: Oral mucosa macrophage
OPMD: Oral potentially malignant disorders OSCC: Oral squamous cell carcinoma OTSCC: Oral tongue squamous cell carcinoma PAMP: Pathogen-associated molecular pattern PCR: Polymerase chain reaction
PD-1: Programmed cell death protein-1 pDCs: Plasmacytoid DCs
PDL-1: Programmed cell death ligand-1
PTPRC (gene for CD45): Protein tyrosine phosphatase receptor type C
RANKL: Receptor activator of nuclear factor kappa-B ligand
REK: Regional ethical committee scRNAseq: Single cell RNA-sequencing skinLP: Skin/dermal lichen planus s-LCs: Skin LCs
SLIT: Sublingual immunotherapy
TAP: Transporter associated with antigen processing Tc cells: Cytotoxic T cells
TCRs: T cell receptor Tem: Effector memory T cell TF: Transcription factor
TGFB: Transforming growth factor receptor β Th cells: T helper cells
Tip-DCs: TNF and NO producing dendritic cells TMA: Tissue microarray
TME: Tumor microenvironment TNF: Tumor necrosis factor Treg: T regulatory cell
TRM: Tissue resident macrophage
UICC: Union for International Cancer Control vst: Variance Stabilizing Transformation WHO: World health organization β2M: β2-microglobulin
INTRODUCTION The oral mucosa
The oral mucosa it the soft tissue lining of the oral cavity, extending from the vermillion border of the lips to the palatopharyngeal folds (1). As the oral mucosa is exposed to a vast amount of different substances, like food, toxins and a variety of pathogenic and commensal microbes daily, its barrier functions are fundamental to maintain tissue homeostasis (2, 3).
The outer barrier of the oral mucosa includes the stratified squamous epithelium that covers the surfaces, which forms a physical barrier against the oral environment (Figure 1).
Figure 1. Histologic and schematic image of the buccal mucosa. Scale bar = 100 μm. Reproduced from (4), with permission.
The epithelium varies in degree of keratinization according to the different niches within the oral cavity (1). Non-keratinized epithelium is found in some areas, like the soft palate, the floor of the mouth, the buccal (Figure 1) and labial mucosa, while the gingiva and the hard palate are keratinized in order to resist the stress of mastication (1, 5). The dorsum of the tongue is lined with a specialized epithelium, consisting of taste buds and lingual papillae, and it can be keratinized or non-keratinized.
Epithelial projections, called rete pegs, extend into the underlying lamina propria. The basal layer of the epithelium, the stratum basale, is tightly bound to the acellular basement membrane, the boundary between the epithelium and the connective tissue of the lamina propria (1, 5). Here, oral mucosal melanocytes are found scattered between the basal keratinocytes in a ratio of 1:15 (6). The lamina propria consists of collagen and elastic fibers, with scattered blood vessels, nerves and occasional immune cells. The submucosa, a loose connective tissue with nerves, vessels and variable amounts of adipose tissue, glandular tissue and striated muscles, is seen basal to the lamina propria in some areas of the oral cavity (1). In addition to the physical barrier of the epithelium, saliva, secreted by the salivary glands, plays an important role in rinsing of the oral surfaces. Saliva also provides important antimicrobial substances, like serum IgA, mucins and β-defensins (7). While few immune cells are expected to be seen in standard hematoxylin eosinophil sections of the oral mucosa, antigen- specific immune staining, flow cytometry and single-cell RNA sequencing have revealed that the
leukocyte compartment is heterogeneous. Populations of Langerhans cells (LCs), macrophages (MFs), dendritic cells (DCs), lymphocytes, plasma cells, natural killer (NK) cells and neutrophilic granulocytes are present in different fractions of different anatomical compartments of the oral mucosa (1, 8-10).
Those cells play essential roles in mounting appropriate immune responses against different types of antigens encountered.
In health, the oral mucosa provides an environment in which pathogens are eliminated, food and self- antigens are tolerated, and commensal microorganisms are allowed to colonize (11). However, remarkably little is known about the group of immune cells that are crucial in distinguishing between
“friends and foe” in the oral mucosa in health, the so-called antigen presenting cells (APCs).
As for other barrier tissues, disturbances in the delicate homeostatic balance in the oral mucosa may cause disease, like chronic inflammatory or autoimmune diseases (12, 13). To understand the role of APCs in these diseases, it is fundamental to understand the cells’ presence and role in the healthy mucosa.
The oral epithelium is also exposed to a variety of potential chemical carcinogens, which may cause mutations in the genome of the basal cells of the epithelium and ultimately lead to oral cancer, predominantly squamous cell carcinoma (14-16). As part of the tumor microenvironment (TME), immune cells are thought to play a role in all phases of cancer development. By cell-to-cell contact and cytokine secretion, they can provide extensive crosstalk with both normal cells and cancer cells, which may modulate their phenotypes, leading to pro- or anti-tumorigenic behavior (17, 18). Immune cells can modulate signaling pathways and transcription factors (TFs) of the target cells. Such dysregulation is a common feature of cancer cells, and today, the identification and verification of molecular changes in such pathways have been successfully used as prognostic biomarkers in some cancers (19, 20).
However, this has not been applied for oral cancer in which reliable prognostic biomarkers still are missing. With regard to the poor prognosis of oral cancer, current prognostic biomarkers need to be replaced by new prognostic biomarkers that allow improved stratification of the patients into different treatment strategies (21).
The immune system
The immune system can be separated into two arms: the innate and the adaptive. The innate immune system is the first line of defense against antigens entering the body and includes tissue resident macrophages (TRMS), neutrophilic granulocytes, NK cells, mast cells and humoral factors like complement (22, 23). Components of the innate immune system recognize molecules that are frequently found in pathogens (PAMPs, pathogen-associated molecular patterns), or that are released by damaged cells (DAMPs, damage-associated molecular patterns) (24). As the innate immune system reacts independently of antigen, it is often also called “the non-specific immune system” (22).
Acquired, or specific, immune defenses rely on hematopoietic stem cell-derived B and T cells, which express clonally unique antigen receptors (BCRs and TCRs) that recognize and respond specifically to different antigenic epitopes. (25). Upon activation, B cells differentiate into plasma cells which produce antigen specific antibodies (26). T cells comprise CD8+ cytotoxic T (Tc) cells and CD4+ helper T (Th) cells.
Tc cells perform direct killing of infected cells, while Th cells provide support to B cells and Tc cells, and activate cells of the innate immune system (23). While B cells recognize antigen directly, T cells are dependent on a process called “antigen presentation”, carried out by a range of specialized cells, called
“antigen presenting cells” (APCs) (27).
In this thesis, I have focused on APCs and therefore the process of antigen presentation, types of APCs and their functions will be further elaborated.
Antigen presentation is mediated by major histocompatibility complex (MHC) class I and MHC class II molecules (Figure 2) (28).
Figure 2. Antigen presentation by MHC I and MHC II complexes. a) Antigen presentation mediated by MHC class I complex.
Antigens present in the cytoplasm, such as virus or tumour antigens are processed and bound to the MHC I molecule, before transport of the antigen-MHC I complex to the cell surface. The MHC class I-antigen complex is recognized by CD8+ T cells. b) Endosomal antigens from extracellular sources, such as bacterial antigens, are processed by and loaded onto the MHC class II molecules, generating the MHC class II complex, which presents antigens to CD4+ T cells. MIIC, MHC class II compartment;
TAP, transporter associated with antigen processing; TCR, T cell receptor; CLIP, class II-associated invariant chain peptide;
β2M, β2-microglobulin; ER, endoplasmatic reticulum; NLRC5, NOD-, LRR- and CARD-containing 5, LMP2;subunit of proteasome. Figure reproduced from (29), with permission.
MHC class I molecules are found on the surface of all nucleated cells in the body and present intracellular antigens to CD8+ T cells, for example from viruses (30). MHC class II molecules are, however, only found on a group of cells called “professional antigen presenting cells”, or often “APCs”
for simplicity. These includes macrophages, dendritic cells, Langerhans cells and B cells, the three
former being the most prominent APCs in the oral mucosa (9, 27, 31). APCs have the ability to recognize and engulf extracellular antigens, for instance from bacteria, process them, and present antigenic peptide fragments bound to MHC II molecules to Th cells. While tissue MFs mainly perform antigen presentation to effector- or memory Th cells locally in the tissue, DCs and LCs have the capacity to migrate to the regional lymph nodes (LNs) through afferent lymph vessels and activate naive Th cells (32-34). A naive CD4+ T cell in the lymph node that is encountering its specific antigen presented by a migrating APC, can differentiate into several different effector subsets. The best studied Th subsets are Th1, Th2, Th17, and T regulatory cells (Tregs), which all secrete specific cytokines coordinating different immune responses (Figure 3) (35).
Figure 3. Overview of the main T helper subsets activated by an APC, in this case a dendritic cell presenting antigen to naive CD4+ T cells via major histocompatibility complex (MHC) class II molecules. During this process, specific cytokines drive differentiation and clonal expansion of CD4+ T cells into functionally distinct effector T helper (Th) subsets. Figure reproduced from (36), with permission.
The type of antigen as well as local cues, e.g. from the cytokine milieu in the region of antigen capture, are integrated by the APC and influences the T cell differentiation into the distinct effector Th subsets.
Following activation, CD4+ effector T helper cells migrate back to the peripheral effector sites as effector T cells and promote an immune response customized to the type and level of threat (37).
Antigen presenting cells of the oral mucosa
The main APCs in the oral mucosa are macrophages, dendritic cells and Langerhans cells (9). A brief introduction to the current knowledge regarding their diversity, ontogeny and functional characteristics follows below.
Macrophages (MFs) are evolutionary conserved phagocytes discovered by the Russian-borne physiologist and zoologist Elie Metchnikoff after a set of famous experiments on starfish larvae in the late 19th century (38). Today, 140 years after their discovery, tissue resident MFs (TRMs) are known to reside in nearly all tissues in the body, were they play important roles in maintaining homeostasis (39- 42). Besides their great ability to engulf and eliminate pathogens, TRMs play diverse roles in many physiological processes, including clearance of cellular debris and tissue remodeling (43, 44). TRMs may have an embryonic origin, or they can originate from adult bone marrow-derived monocytes. In the case of inflammation, monocytes are recruited to inflamed tissues in large numbers where they differentiate into functionally different subsets, influenced by the local cytokine milieu in the tissue (45). With time, such monocyte-derived MFs can acquire a TRM phenotype (46).
The traditional functional classification of MFs in proinflammatory M1 MFs, and tolerizing and tissue remodeling M2 MFs is based on in vitro cytokine stimulation of monocytes, and does not readily reflect the more complex biological situation in vivo. Moreover, a function-based classification of macrophages is not optimal, since there is substantial functional overlap between macrophage and DC subsets (47). However, origin-based nomenclature may be too simple, as both embryonically and adult bone marrow derived monocytes may give rise to macrophages with overlapping transcriptomes (48, 49). Heterogeneity of MFs can be caused by imprinting of recruited monocytes from the local cytokine milieu, and thus, both the anatomical region and the time spent in the tissues are thought to be decisive of macrophage phenotype (46). Since macrophage heterogeneity may stem from such lineage-imprinted differences between recently recruited transient monocyte-like MFs and TRMs, these terms are now often used for classification (50, 51).
The increased use of single-cell RNA sequencing (scRNAseq) has revealed the existence of multiple MF subsets in various tissues (50, 52, 53). In the gut, a striking heterogeneity of MF subsets has been revealed, including several transcriptomically distinct monocyte-like MFs and TRMs (50, 54).
Less is known about the human oral mucosa MF network. Dutzan et al. have characterized the immune network in human gingiva and human buccal mucosa using flow cytometry (9). They detected a population of DC/MF among the leukocytes in both buccal and gingival mucosae. In healthy gingiva, this population was characterized further. Here, the majority of APCs were CD14+, including HLADR+CD14+ autofluorescent (AF), resident MFs and HLADR+CD14+AF− migratory monocytes.
However, a detailed characterization of the MF subsets in the human oral mucosa is currently lacking.
Dendritic cells (DCs)
DCs were discovered in 1973 by the Canadian immunologist Ralph Steinman. In his initial paper, Steinman described a rare cell type in peripheral lymphoid organs of mice, with characteristic movements and a cell body displaying dendritic processes (55). He suggested the name “dendritic cells” for these cells. The next 20 years, Steinman continued his study of DCs and published many papers that revealed the central role of dendritic cells as the most potent APCs, with a unique ability to activate naive T cells (56). Steinman was awarded a share of the 2011 Nobel Prize in Medicine or Physiology, after his death, for his discovery of dendritic cells.
DCs are distributed in peripheral and lymphoid tissues (57-59). A small proportion are also circulating in the blood (60, 61). DCs are unique in their role, connecting the innate and adaptive immune systems.
Upon recognition of a pathogen, tissue resident DCs engulf pathogens by receptor-mediated phagocytosis or micropinocytosis. Like MFs, DCs process extracellular and intracellular proteins and present peptide antigens on MHC molecules. However, DCs excel in their ability to migrate to the regional lymph nodes where they activate and polarize naïve T cells, and thus, shape pro-inflammatory or tolerogenic responses (59).
The heterogeneity and origin of human DCs are not fully understood. The most thoroughly characterized populations are plasmacytoid DCs (pDCs) and two functionally specialized subsets of myeloid conventional DCs, cDC1 and cDC2 (59). Monocytes can differentiate into monocyte-derived DCs (moDCs) in vitro (47). CD163+ CD14+ DC-like cells have been detected in vivo and were until recently given different names like inflammatory DCs (iDCs), TipDcs and moDCs, but the origin of these cells has just recently started to be resolved (62-65). Moreover, the use of single cell RNA sequencing has led to the emergence of several new subsets which have been given different names in different studies, often based on the expression of a certain marker (66-69). This led to confusion in the field, and raised the question of whether these cells represented true subsets or cell states induced in response to environmental stimuli (70). Recently, Ginhoux et al. reviewed these different single cell RNA- sequencing (scRNAseq) studies and found that DC subsets other than cDCs and pDCs could be classified in two groups. The authors suggested that the term DC3 should be used for the CD163 DC-subset (previously iDCs). DC3s have been shown to have a progenitor distinct from that of cDC1s and cDC2s and thus represent a true subset. The term “mregDC” was suggested for a particular cell state that could be attained by cDC1 and cDC2 upon migration to regional lymphoid tissue (70).
Origin of DCs
All DCs are derived from hematopoietic stem cells, and the branching into distinct lineages during hematopoiesis is driven by different transcription factors (TFs) (71-74). However, in humans, the ontogeny, diversity and functional characteristics of all DC subsets are not fully understood. An overview of the current view on hematopoiesis is shown in Figure 4.
Figure 4. “The revised model of hematopoiesis”. In this model, the gates defined by CD38 (blue borders) an CD45RA (red borders) contain phenotypically related cells, but with subsets of cells with restricted potential for their respective lineage (indicated by the fill colors within the gates). The granulocyte-macrophage progenitor (GMP) contains a heterogeneous cell population with respect to cell potential. The IRF8+ CD123+ GMP population gives rise to pDC, cDC1 and DC2, while DC3 and monocyte potential is restricted to the CD33+ IRF8lo progenitor. Dark red and turquoise shading indicate the requirement for the TFs GATA2 or IRF8, respectively, and the color intensity reflects the level of expression of these markers. Figure reproduced from (75), with permission.
PDCs and cDCs arise from an IRF8+ CD123+ granulocyte MF progenitor (GMP), and their development depends on the growth factor tyrosine kinase 3 ligand (FLT3L) and its receptor FLT3 (76, 77). Further branching into pDCs, cDC1s and cDC2s is driven by different transcription factors. pDC commitment depends on the TFs Irf8, Tcf4 (E2-2) and Zeb2 while cDC1 commitment requires Irf8, Id2 and Batf3 (78- 81). Lineage specification of cDC2 requires Irf4 and Zeb2 (78, 82). DC3s do not differentiate via cDC (CDP)- or monocyte-restricted (cMoP) progenitors, but from a fraction of IRF8lo CD123loGMDPs redundant of Flt3L (62, 83).
Functional characteristics of DC subsets
pDCs circulate in the blood, and are rarely detected in healthy peripheral tissues, but may be present in disease (84, 85). Unlike myeloid cDCs, they do not express the myeloid antigens CD11c, CD33, CD11b or CD13, but can be detected based on their expression of classical pDC markers like CD303 (Clec4C;
BDCA-2), CD304 (neuropilin; BDCA-4), CD85k (ILT3) and CD85g (ILT7) (86). They do not constitutively present cell-associated antigens to T cells, but perform their main function by the production of large amounts of type I interferon in response to virus infections (59, 87).
cDC1s are present in low numbers in blood and peripheral tissues (88, 89). Both cDC1 and cDC2 express CD13 and CD33, but cDC1 express low levels of CD11c and Sirp-α (CD172) compared with cDC2. Moreover, cDC1s express high levels of BTLA, CADM1 and indoleamine 2,3 dioxygenase, as well as high intracellular IRF8 expression and lack of IRF4 (90). Unlike monocytes, cDC1s are CD14- (59). CD141 is highly expressed on cDC1s, but is not specific for this subset, since cDC2 can
upregulate CD141 under certain conditions. The C-type lectin domain containing 9A (Clec9A) and the X-C Motif Chemokine Receptor 1 (XCR1), however, are highly conserved and specific markers for cDC1s (91, 92).
Functional properties of cDC1s include uptake of apoptotic cells by Clec9A (93). Moreover, cDC1s are major producers of type I and type III Interferons (IFN-α and IFN-δ) and are also known to promote Th1 and NK responses through IL-12 (90). Moreover, cDC1s excel in cross-presentation as compared with cDC2, which refers to their ability to present exogenously derived antigen to the CD8+ T cells, by transfer of antigen to MHC class I, instead of MHC class II pathway (94). cDC1s are therefore equipped to induce immune responses against viruses and intracellular bacteria (95-97). However, while their cross-presenting capability seem to be restricted to cDC1s in mice, it is highly debated whether human CD1c+ are exclusive in their cross-presenting ability, since both cDC2s and monocyte-derived DCs have been shown to have the ability to cross-present antigen in vitro (98, 99). In addition, human studies have shown that secretion of IL-12 by cDC1s is inferior to that of monocytes and cDC2, and thus, their IL-12-derived Th1-activating capability may be inferior to that of the latter subset in human (59, 90).
cDC2s are the major population of human cDCs in blood and peripheral tissues (59). They express high levels of CD1c, CD1a, FcεRI, Clec10A and Sirp-α. However, unlike cDC1s, there are no specific markers for cDC2s. IRF4 is considered lineage-defining for cDC2s, and can distinguish cDC2s from IRF4- IRF8+ DC1s (100). However, to distinguish cDC2s from monocytes, IRF4 expression must be combined with absence of classical monocyte/MF markers, since monocytes are shown to express IRF4 under certain situations (59).
With their wide range of lectins, toll-like receptors (TLRs) and other pattern recognition receptors, cDC2s are well equipped for efficient detection and uptake of different types of antigen (59). They respond well to lipopolysaccharide and flagellin through TLRs 1–8, and have a potential of capturing mycobacteria with CD1a and-c, which remains to be assessed (101). Moreover, cDC2s express Dectin- 1 (Clec7A) and dectin-2 (Clec6A) which suggests a possible role in combating fungi (102).
cDC2s are potent stimulators of naive CD4 T cells, but have inferior capacity to cross-present antigen to CD8 T cells compared with cDC1s (90). In vitro, human cDC2 are potent in the activation of several T cell subsets, including Th1, Th2, Th17 and CD8+ T cells, suggesting the capacity to promote a wide range of immune responses in vivo and highlighting the plasticity of cDC2s in different contexts (90, 103, 104).
The knowledge of DC heterogeneity in human oral mucosa is sparse. Dutzan et al. have identified a DC/Mac population in both gingiva and buccal mucosa by flow cytometry. While this population was not further characterized for buccal mucosa, in gingiva, a small population of cDC2 and a minor population of cDC1s were identified (9).
The German physiologist Paul Langerhans discovered LCs in 1868. Because of their characteristic long dendrites, he originally suggested LCs to be part of the nervous system (105). The discovery of LCs as migrating cells, potent in activating naïve T cells, led to the classification of LCs as dendritic cells (106, 107). Recently, it has become clear that skin LCs share origin with tissue resident MFs, and thus were reclassified as MFs (107). This will be discussed in more detail below.
LCs are unique antigen presenting cells in a niche-specific location in the epithelium of barrier tissues like the skin, corneal, vaginal, nasal and oral mucosa (9, 108-110). While LCs from these different tissues are transcriptionally and functionally quite similar, small variations are thought to stem from niche-specific imprinting from the local environment (111). LCs express high levels of the C-type lectin langerin and the MHC I molecule CD1a (59). Moreover, they contain Birbeck granula which are suggested to be involved in endosomal trafficking and in which langerin accumulates (112). While both langerin and Birbeck granula previously were thought to be specific for LCs, it is now known that cDC2s spontaneously upregulate langerin in peripheral tissues, and monocytes my upregulate langerin in vitro (113).
Residing in the outermost epithelium of barrier tissues, LCs are the first APCs to encounter antigens that penetrate into the epithelial layers, and they are thus uniquely positioned to perform T cell activation. LCs share migratory potential with DCs, and may activate naive T cells in the regional lymph nodes (107). However, to grasp LC function based on literature is a challenging task. One of the main reasons for this is the relatively recent acknowledgement that the previously assumed LC-specific langerin also may be expressed on other cells (114) . Thus, studies before 2006 conducted on sorted langerin+ cells or from different langerin-depleted mouse models may have drawn erroneous conclusions on LC function and should be interpreted with caution (107, 115). While LCs previously were believed to play key roles in recruitment of anti-hapten T cells driven contact hypersensitivity, these are now found to be mainly langerin+ dermal DCs (107). Studies on sorted LCs from human peripheral tissues should also be interpreted with caution, keeping in mind that imperfect exclusion of langerin+ DC2s may have influenced the results (115). While still much is unknown regarding LC function, including non-redundant functions, the current view of (skin) LC function includes both tolerogenic and pro-inflammatory actions (107). This view is visualized in Figure 5, and outlined below.
Figure 5. Skin LC functions. Figure reproduced from (107), with permission.
In response to small breaches in the upper layer of the epithelium, LCs extend their dendrites towards the epithelial surface and survey antigens that have penetrated the keratin layer of the epithelium. LCs may induce humoral antigen-specific IgG1 responses, often called “pre-emptive immunity”, against such captured antigens. Upon larger disruptions of the surface, LCs may encounter pathogens that have invaded into the epithelium (107). Like DCs, LCs have the ability to migrate to the regional lymph node and activate naive T cells. Studies have demonstrated the skewing of Th subset proliferation in different directions, for instance Th17 response after Candida albicans infections, and Treg expansion after ionizing radiation of skin (116). However, as TRMs, skin LCs can also activate T cells locally in the tissue. A study of Kupper et al. demonstrated, using only autologous cells, that resting LCs induce selective proliferation of resident skin Treg cells. However, upon capture of a pathogenic antigen, LCs induce proliferation of effector memory T (Tem) cells (117). Thus, the view that LCs mostly have a tolerogenic function in steady state, but have the capacity to stimulate inflammatory effector T cells in the case of infection, has now been widely accepted.
While functional plasticity may be one reason for the variety of functional characteristics suggested for LCs, another explanation may stem from the until recently unrevealed heterogeneity of LCs (118).
Four LC subsets (s-LCs) have recently been reported, based on a distinct sets of signature genes, named LC1, LC2, activated LCs (a-LCs) and migratory LCs (mig-LCs). Two of these, LC1 (CD207hi CD1A+) and LC2 (Clec10AhiCD14+ITGAMhi) are immature LCs, while the a-LCs and the mig-LCs show higher expression
of maturation markers. Mig-LCs show a high relative expression of migration markers as compared with the other LC subsets. Whether a similar heterogeneity reported for skin LCs exist for oLCs, is unknown.
Skin LCs (sLCs) are more extensively studied as compared with their oral counterparts. Little is known about human oLC origin, replacement kinetics, heterogeneity and function. However, a recent study has reported that murine oLCs play a key role in preventing alveolar bone loss, by inhibiting RANKL+CD4+ T cells (119). Moreover, studies from mice have suggested major differences in the origin of skin and oLCs (120).
Origin of oral mucosa Langerhans cells
Skin LCs have lately been reclassified from being DCs to be MFs, based on their shared origin with other TRMs like microglia in the brain (107, 121). Moreover, this tissue resident population of LCs self-renew in steady state, without need for replacement by hematopoietic precursors (107). The origin of human oral mucosa LCs (oLCs) is not known. However, studies from mice indicate an LCs origin from bone marrow-derived precursors both from the monocyte- and the dendritic cell lineage which acquire a LC phenotype locally in the epithelium in a TGFB-ALK5-dependent manner (Figure 6) (122). Unlike skin LCs, murine oLCs are constantly replaced by such precursor cells in steady state (120). How this translates to human oLCs is not known.
Figure 6. Overview of origin of murine LCs in skin and oral mucosa. Figure reproduced from (120) , with permission.
Knowledge on the functional characteristics of human oLCs is scarce, but oral LCs have shown a higher stimulatory capacity than skin LCs (123).LCs are suggested to be involved in several oral diseases, like
gingivitis, periodontitis, oral hairy leukoplakia and graft versus host disease (GVHD), mostly based on reports on their numbers being different from those of healthy controls (124-127). Several studies have reported increased numbers of LCs in oral lichen planus (OLP), a chronic inflammatory disease of the oral mucosa.
Oral lichen planus (OLP)
OLP is a relatively common chronic inflammatory disease with a prevalence of approximately 1 % (128).
It is most common among the middle-aged and the elderly, and affects females more often than males (129). OLP is most frequently seen in the buccal mucosa, but gingiva, tongue and labial mucosa can also be affected. Lesions of the palate and the floor of the mouth are rare. Six different variants of OLP are categorized based on their clinical appearance, namely reticular, erosive, atrophic, plaque-like, papular and bullous, the latter being particularly rare (130, 131). The reticular variant is the most common, and typically appears as bilateral white striae called Wickhams striae, organized in a grid-like pattern, eventually combined with erosive areas and ulcers (131, 132). The symptoms range from no symptoms to considerable discomfort and pain, often after intake of spicy food (131, 133).
Erosive/atrophic variants of OLP are associated with more severe symptoms than plain reticular lesions (134). While the oral mucosa may be the only anatomical site of involvement, around 15 % may also have cutaneous and 25 % genital lesions (135). Histologically, OLP lesions are characterized by an inflammatory infiltrate dominated by T cells immediately beneath the epithelium, comprising both CD4+ and CD8+ T cells. (136, 137). Furthermore, a variable degree of keratinization, liquefaction degeneration of the basal cells and a “saw tooth” appearance of the epithelial rete ridges are often seen. Apoptotic keratinocytes may be seen as eosinophilic “Civatte” bodies (131). Oral lichenoid lesions (OLL) are used for disorders that may have a similar histological picture, including oral lichenoid contact hypersensitivity reactions and oral lichenoid drug reactions. In OLL, there may be scattered plasma cells and deeper perivascular lymphoid aggregates may be noted (138).
The pathogenesis of OLP is not fully understood. However, it is suggested to be an autoimmune response against unknown antigens expressed by the keratinocytes at the lesional site (139). Apoptosis of keratinocytes is suggested to be triggered by CD8+ T cells, but the mechanism remains unknown (140). However, the cytokine milieu provided by different subsets of CD4+ T helper cells is known to play a role in the pathogenesis of a variery of inflammatory diseases (141). A robust characterization of the T cell subset composition in the inflammatory infiltrate is currently lacking, but several Th subsets including Th1, Th2, Th17 and Tregs have been suggested to contribute to the pathogenesis (142, 143). Interestingly, a recent study reported improvement of OLP after treatment with the IL-17 inhibitor secukinumab. Moreover, targeting cytokines associated with the Th17 axis, e.g. with anti-IL- 23 or anti-IL-12/IL-23, lead to marked and prolonged improvement of mucosal lesions in OLP, indicating a role for the Th17 subset as a potential driver of the disease (144).
As major orchestrators of the T helper cell subsets, APCs may play a key role in the pathogenesis of OLP (129). Several studies reported increased numbers of epithelial LCs and LC-like cells in the subepithelial infiltrates of OLP (110, 145-147). However, the origin of these LCs and LC-like cells remains unknown. Knowledge of the origin of cells involved in a disease is an essential step in the understanding of its pathogenesis, and thus, the origin of langerin+ cells in OLP should be determined.
Besides the role of immune cells in tissue homeostasis, infectious and chronic inflammatory diseases, immune cells are also involved in cancer development and progression. Although disputed, OLP is classified as a potentially malignant lesion by WHO, with a slightly increased risk of malignant transformation into oral squamous cell carcinoma (OSCC) (129, 148). Long-standing chronic inflammation has been considered to support cancer development (149). Thus, increased knowledge of the chronic inflammatory infiltrate in OLP involved can be important, not only for understanding the
development and progression of OLP, but also for deciphering the immunological contribution to a microenvironment where oral squamous cell carcinoma are more likely to arise.
Oral tongue squamous cell carcinoma (OTSCC)
Clinically, OSCC often present as non-healing ulcers with indurated borders on the mobile tongue (anterior 2/3), the floor of the mouth, and the buccal/labial, gingival, hard palate or alveolar mucosa (150). Distinguishing OSCC of the mobile tongue (OTSCC) from OSCC of the posterior 1/3 (basal tongue) is important, since the latter belongs to a different anatomical subsite, the oropharynx. Here, squamous cell carcinomas are associated with different etiological factors, treatment strategies and prognosis than OTSCC (151).
Globally, cancer of the oral cavity and lip, classified together, accounted for 2 % of all human malignancies in 2020 (152). OSCC constitute 90 % of all cancers of the oral cavity (152, 153). The incidence varies between geographical regions, with the highest incidence seen in regions of Asia. The high prevalence in these areas reflects the habit of using tobacco products, both smoking and smokeless (in the form of betel quid) (154, 155). In Norway, 224 new cases of oral cancer were registered in 2020 (156). The oral tongue is reported to be the most common subsite, accounting for about 45 % of OSCC diagnosed in Norway on 2005-2009 (157).
Several studies from different parts of the world have reported an increase in the incidence of OTSCC (158-162). In Norway, the national cancer register has classified the mouth and oropharynx together in the report of incidence trend rates from 1965-2021 (Figure 7) (156). Here, the incidence is increasing, but the trend selective for OTSCC in Norway during this period is not known. Intriguingly, recent reports from different countries have indicated that the epidemiology of OTSCC seems to change. An increased incidence of OTSCC in a subgroup of patients < 45 years old without the classical risk factors of tobacco use and alcohol consumption is reported, also in Finland (161, 163).
Figure 7. Trends in incidence and mortality rate for cancers in mouth and pharynx (ICD-10 C00-14) in Norway from 1965- 2021. Figure reproduced from (156), with permission, and available from https://www.kreftregisteret.no/globalassets/.
Histologically, the conversion of normal basal keratinocytes into malignant cells is suggested to follow a stepwise process through hyperplasia, dysplasia (mild, moderate and severe) and carcinoma in situ
(164). Oral potentially malignant disorders (OPMD), in which dysplasia and OSCC are more likely to develop include leukoplakia, erythroplakia, oral submucous fibrosis, proliferative verrucous leukoplakia, OLP, actinic keratosis, palatal lesions in reverse smokers, oral lupus erythromatosus, dyskeratosis congenital, oral lichenoid lesion and oral graft versus host disease (148).
Globally, the main risk etiological risk factors for the development of OPMD and OSCC/OTSCC is the use of tobacco in different forms (165). Tobacco and alcohol may have a synergistic carcinogenic effect, by ethanol having a permeabilizing effect on the oral epithelium, thereby facilitating penetration of tobacco carcinogens (166). Other risk factors include oncogenic viruses, poor oral hygiene, and genetic predisposition (165, 167-169). However, the etiological risk factors underlying OTSCC development in young individuals without a history of smoking or excessive alcohol intake is not known. While Human papilloma-virus (HPV) is a common risk factor for cancer of the oropharynx, the involvement of HPV as a risk factor for OTSCCs is highly disputed (170, 171). In the study of OTSCC diagnosed in Norway between 2005 and 2009, all carcinomas were HPV negative (172).
In Norway, surgical resection, with or without postoperative adjuvant radiation therapy (RT) is the primary treatment for OTSCC. Chemotherapy may be used in advanced stages. However, only 8 % of OTSCC cases diagnosed in Norway between 2005 and 2009 received chemotherapy (157). Several immunotherapy strategies have been developed for head and neck squamous cell carcinoma (HNSCC) during the last two decades, including immune checkpoint blockade (ICB) (173-175). Checkpoints are signals for regulating the antigen recognition of T cell receptor (TCR), and are thus crucial to prevent CD8+ T cells from destroying normal cells. One checkpoint is the programmed death receptor/-ligand (PD-1/PD-L1)- interaction, which inhibits direct killing of infected cells and cancer cells by CD8+ T cells.
Cancer cells often upregulate PD-1 to increase such inhibition and thus avoid CD8+ T cell-mediated killing. In therapy, anti-PD-1 or -PD-L1 monoclonal antibodies prevent such inhibition. Pembrolizumab is one of three PD-1-targeting ICB which are approved by the USFDA (The United States Food and Drug Administration) for treatment of recurrent and metastatic (R/M) HNSCC (176). This approval was based on large randomized trials, also including Norwegian patients (177, 178). However, a criterion for treatment with pembrolizumab is that PD-1 is expressed in a significant fraction of the tumor tissue, and thus, only a selection of OTSCC patients can receive this treatment. In Norway, pembrolizumab was approved for first line treatment of R/M HNSCC for patients, including OTSCC, in 2020 (179, 180).
Globally, the prognosis of OTSCC is considered to be relatively poor, with a reported 5-year survival of 65 % (162, 181). In Norway, the 5-year disease specific survival was 54 % in OTSCC cases diagnosed between 2005-2009 (157). While the prognosis of OTSCC has been shown to both improve and decrease in different countries over the last decades, such estimates are lacking for OTSCC Norway.
In the Norwegian cancer registry, trend rates for 5-year relative survival are reported for mouth and pharynx combined (Figure 7) (156). Here, there is a trend of an increasing survival rate over time.
However, whether this also is the case for OTSCC separately, is not known. A potential decrease in OTSCC prognosis over time may be masked by improved prognosis of oropharynx cancer, as reported for other Scandinavian countries (182).
Since treatment with ICB is only recently implemented in the treatment of HNSCC in Norway, it is still unknown how this will influence the prognostic outcome. However, resistance to anti-PD-L1 therapy is common, and a recent study reported that only 15-20 % of ICB treated HNSCC patients respond to
this treatment (183). Considering that only a small fraction of the patients are likely to meet the criteria for receiving pembrolizumab, there is a rationale for continued search for strategies for targeted therapy. Moreover, there is a large variation in the aggressiveness of OTSCC, and even patients with small tumors without lymph node metastases may experience recurrence and death (184).
Tumor staging and –grading
Prognostic judgement of the lesion is one of the most important factors for patient care. Besides meeting patients’ need for information of the future outcome of their disease, prognostic estimates are used by health care professionals to perform decisions of management and treatment (185).
Several prognostic staging and grading systems for prognostication of cancer have been developed during the last century. The TNM system and the WHO histological grading system are the two most widely used clinical/histological parameters for O(T)SCC prognostication.
The TNM system
Globally, the staging system most widely used for cancer prognostication, including for OTSCC, is the American Joint Committee on Cancer (AJCC) TNM system. Here, the extent of the disease is classified to predict the prognostic outcome of malignant tumors (Table 1). The letter “T” refers to the size of the primary tumor and is graded from Tx-T4. The letters “N” and “M” refers to the presence or absence of regional lymph Node and distant metastases, respectively (186) (Table 1).
From the development of the TNM system in 1968, it has continuously been monitored for its accuracy in estimating prognosis in different cancer types, and several new editions have been released. In the 8th edition of TNM published in 2017, two major changes were made regarding oral cancer.
Extracapsular spread was included in the N-stage and depth of invasion (DOI) was included in the T stage (187). DOI refers to the histological measurement of the depth of which a tumor invades into the tissue, and has been shown to be an important predictor for lymph node metastasis in early stage OSCC (Table 1) (188, 189).
Despite that the TNM system is considered to be the gold standard for OSSCC prognostication, several studies have reported that it is suboptimal for predicting the prognostic outcome in patients with OTSCC (190, 191), and that better prognostication systems are needed in order to provide more accurate estimates of survival outcome for individual patients.
Table 1. The 5th edition of the TNM classification for oral cavity cancer (used in the NOROC study (157)) and changes applied in the 8th edition. Reproduced from (192), with permission.
WHO Histopathological grading
The first histopathological grading of SCCs was developed by Broders in 1920 (193). Based on the fraction of differentiated cells compared within the entire tumor cell population in lip SCC, he graded the tumors from I (well differentiated) to IV (anaplastic). After testing the system on several epithelial malignancies throughout the body, the grading system was rapidly acknowledged and implemented in the clinic (194). The scoring system was later adopted and slightly modified by the WHO, and grading of tumors into I-III (well, moderately and poorly differentiated) are often used to classify malignant tumors (195, 196). However, several studies have reported poor correlation between histological grade and prognostic outcome of OSCC tumors, including OTSCC. Several new grading systems have been proposed in order to improve the prognostication value grading of OSCC (197, 198). However, even though some of these have been shown to be promising in OSCC prognostication and treatment determination, none have been accepted for clinical use (199, 200). The Histological Risk model was introduced by Brandwein-Gensler et al. in 2005 (201). This scoring system includes evaluation of the TME. Brandwein-Gensler et al. reported that patients with a denser lymphocytic infiltrate in their OTSCC had a better prognostic outcome than patients with little or no lymphocytic host response (201). A similar association was reported by Bjerkli et al. (202).
Pathogenesis of OTSCC
Cancer development is a stepwise process were accumulation of mutations in genes controlling growth and survival progressively turn normal basal keratinocytes into malignant cells. Cancer cells share a number of common features, called hallmarks, including resistance to apoptosis, sustained angiogenesis and unlimited replicative potential. These hallmark characteristics provide advantages to cancer cells over normal cells, leading to “Darwinistic selection” on a cellular level. However, the path that leads to these common hallmarks varies, both between cancer types and between tumors of the same cancer type (203). TFs are downstream targets of different cell signaling pathways, and are key contributors to tight regulation of differentiation and growth, including control of cell cycle.
TFs are often deregulated in cancer, and may thus have a potential as prognostic biomarkers (204).
Accumulated evidence from recent decades supports a model where the TME, including the inflammatory cells, play a crucial role in cancer initiation and development (17). Such crosstalk between tumor cells and signals provided from inflammatory cells of the TME may have both tumor- suppressive and pro-tumorigenic consequences (17, 18). Besides the reported association between a dense inflammatory infiltrate and a favorable prognosis, little is known about the inflammatory cells and their effect on TFs in OTSCC. Moreover, the prognostic potential of a combined score of
inflammation and TFs in OTSCC prognostication remains unexplored.
KLF4 in OTSCC
One of the TFs that is suggested to be involved in different cancers, including OTSCC, is Krüppel-like factor 4 (KLF4). KLF4 is a zinc-finger transcription factor normally involved in basic physiologically processes, like cell cycle regulation, differentiation and cell migration (205-208). Little is currently known regarding the crosstalk between KLF4 and inflammatory cells. KLF4 may both stimulate and inhibit the inflammatory process (209, 210). KLF4 expression has been demonstrated to be regulated by inflammatory cytokines (13, 14). KLF4 has been shown to be deregulated in several cancer types, as an altered expression pattern is reported in malignant tumors of several tissue origins compared with normal controls (211-214). Thus, KLF4 may be a potential prognostic biomarker in different cancer types. Two studies have examined KLF4 expression in OTSCC, with conflicting results (215, 216). While this could be the result of methodological differences, a context-dependent role of KLF4 is also possible. In support of the latter view, Li et al. suggested a Janus-faced role of KLF4 in OSCC based on
over-expression and knock-out studies on OSCC cell lines (217). As high inflammation score is associated with improved prognostic outcome in OTSCC (201), it is natural to hypothesize that there is a link between KLF4 expression and inflammation score in OTSCC. This remains unexplored in OTSCC.
Moreover, a study on the prognostic role of KLF4 OTSCC expression, alone or in combination with inflammation score in OTSCC remains to be determined in a Western Europe population. The two previous studies on KLF4 in OTSCC are from Asia, and the results of these studies may not be readily translated to OTSCC from other geographical areas, partly due to differences in etiological factors.
Taken together, more knowledge is needed to fully understand the composition and diversity of APCs and their interaction partners in oral mucosal health. This is fundamental for understanding their role in different oral diseases, and ultimately, for the development of novel therapeutic strategies to treat such diseases. The origin of langerin+ APCs in normal oral mucosa and in OLP are important to assess because of their possible implications in the pathogenesis of this disease. This will also increase basic knowledge regarding the origin and replacement kinetics of such cells in the human oral mucosa.
Finally, the prognostic role of KLF4 tumor expression in OTSCC, alone or in combination with inflammation and other histological parameters, remains to be determined in a Western European population.
Therefore, the aims of the studies in this thesis were:
1. To characterize antigen presenting cell subsets of the human oral mucosa according to new knowledge (Paper I).
2. To determine the origin of increased langerin-expressing cells in healthy oral mucosa and in oral lichen planus (Paper II).
3. To determine the prognostic role of KLF4 expression alone or in combination with histopathological parameters such as tumor differentiation and inflammation, in a multi- center cohort of Norwegian OTSCC specimens (Paper III).
The tissue specimens, the laboratory methods used in the studies and the ethical approvals are summarized in Table 2. A detailed description of material and methods is included in the methods sections of the individual papers.
Table 2. Methods used in the current studies
Paper I - Normal oral mucosa
Material Methods Ethical approvals
scRNAseq data downloaded from the Human Oral Mucosa Cell Atlas portal (oral.cellatlas.io)
Normal oral mucosa biopsies (NOM)
Analyses of scRNAseq data
Regional Ethical Committee (REK sørøst, Oslo, Norway, 2015/1247)
Paper II - Oral lichen planus
Material Methods Ethical approvals
Formalin-fixed, paraffin- embedded (FFPE) blocks OLP (archival) and NOM (surgical)
Immunofluorescence Cell counting Flow cytometry
Regional Ethical Committee (REK sørøst, Oslo, Norway, 2015/1247)
Paper III - Oral tongue squamous cell carcinomas
Material Methods Ethical approvals
Multi-center retrospective study, Norwegian oral cancer (NOROC) study:
Tissue microarray (TMA) blocks
External transcriptomic data
Oral cancer cell lines
Immunohistochemistry-KLF4 Scanning of TMA sections Scoring of KLF4 in OTSCC.
Access to histopathological parameters (whole sections)
Gene Expression Profiling Interactive Analysis software (GEPIA)
GraphPad Prism (https://www.graphpad.com/) software and used for statistical analysis Cell treatment with cytokines and growth factors, and immunocytochemistry (KLF4) Quantification of KLF4
Northern Norwegian Regional Committee for Medical Research Ethics (REK Nord;
2013/1786 and 2015/1381)
SUMMARY OF RESULTS
Paper I - Analysis of single-cell transcriptomic data reveals considerable heterogeneity among human oral mucosa antigen presenting cells
In order to determine the heterogeneity among human oral mucosa APCs, we acquired human oral mucosa APCs using single-cell transcriptomic data from the recently published Human Oral Mucosa Cell Atlas (https://oral.cellatlas.io/). By filtering APCs based on co-expression of PTPRC/CD45 and MHCII, we identified several phenotypically distinct APC clusters based on differentially expressed genes (DEGs). This included one subset of cDC1s, two subsets of cDC2s, three subsets of cDC3s, three subsets of MFs and four subgroups of Langerhans-like cells (oLC1-4). In addition, one subset was transcriptionally compatible with the recently reported mregDC state. Flow cytometric analyses of human oral mucosa biopsies were used to support the findings. The LC-like cell subsets showed transcription profiles that partly overlapped with the transcription profile of the four LC subsets recently detected in skin. Gene ontology analysis oLC1 and 2, were enriched for the GO term
“phagocytosis”, in line with their less activated phenotype compared with oLC3 and oLC4.
Cell-cell interaction analysis revealed a large array of putative ligand-receptor interactions that may underpin the location and differentiation of oral APCs. NOTCH, annexin, semaphorin, AXL and EGFR/FGFR families were broadly displayed. Interactions associated with tissue retention of APCs were mainly found between APCs and melanocytes. Melanocytes displayed several significant interactions with the oAPC clusters, for instance between fibronectin and integrin. Moreover, CADM1:CADM1, CAMD3:CADM1 as well as NECTIN2:CD226 interactions were selectively expressed between melanocytes and cDC1, indicating that melanocytes are important for tissue retention of cDC1s.
Paper II - Origin of langerin (CD207)-expressing antigen presenting cells in the normal oral mucosa and in oral lichen planus lesions
In order to determine the origin of the langerin-expressing APCs according to current knowledge, we examined oral mucosal biopsies from healthy persons and patients with OLP using multicolor immunofluorescence. In NOM, a substantial fraction of Langerhans cells (LCs) expressed Ki-67, indicating that steady-state oral mucosal LCs are at least partially maintained by self-renewal. In OLP, the numbers of LCs were increased but proliferation was not altered, indicating that the increased cell numbers appeared to depend on recruited dendritic cell (DC)-precursors. Moreover, we found a large increase of langerin+ APCs within the lamina propria of OLP patients. Such cells did not display monocyte or MF markers, but rather showed a phenotype compatible with tissue-elicited IRF4+ cDC2.
Paper III - The prognostic role of combining Krüppel-like factor 4 score and grade of inflammation in a Norwegian cohort of oral tongue squamous cell carcinomas
KLF4 expression levels were examined in a multicenter cohort of 128 oral squamous cell carcinoma (OSCC) specimens from the tongue (OTSCC) using immunohistochemistry. We found that a high nuclear KLF4 score in OTSCC were significantly associated with age > 65 years and a well differentiated phenotype of OTSCC. No significant association was found for nuclear KLF4 expression and gender, T- stage, N-stage, clinical stage, pattern of invasion, or tumor budding. A borderline significant association between high nuclear KLF4 expression and a marked stromal inflammation was demonstrated. By use of log rank test and Kaplan Meier plot, we found a trend for a favorable 5-year disease-specific survival for patients with high KLF4 expression as compared with those with low expression. Cases of OTSCC with a marked/moderate inflammation in the tumor stroma had a significantly better 5-year disease- specific survival as compared with patients with slight or no inflammation. Here, the 5-year disease- specific survival rate was 68 %. However, the combination of high levels of KLF4 expression and high
inflammation score identified a subgroup of patients with a significantly better 5-year disease-specific survival as compared with the rest of the OTSCC patient group. Here, 88 % of the patients were alive 5 years after diagnosis. Furthermore, this combination was found to be an independent prognostic marker in contrast to clinical stage, T-stage, and N-stage in a Cox multivariate analysis of 5-year disease-specific survival. In order to explore the pathophysiological background of the observed associations, we performed in vitro stimulations of OSCC cell lines with different inflammatory cytokines and growth factors. Here, IFN-γ-stimulation of OSCC cells upregulated nuclear KLF4 expression suggesting a link between inflammation and KLF4 expression in OSCC cells. In two external KLF4 mRNA datasets (The Cancer Genome Atlas/The Genotype-Tissue Expression Portal), lower KLF4 mRNA expression were found in OSCC and head and neck squamous cell carcinomas (HNSCC) than in control oral epithelium.
General advantages/disadvantages for the main methods used in the studies are summarized in Table 3. Specific methodological considerations of particular relevance for the individual papers are discussed below.
Table 3. Advantages/disadvantages for the main methods used
x Antigens can be visualized in a microanatomical context x Visualization of multiple (2- 10) antigens simultaneously x Quantification more accurate
x Cost and time effective x Formalin-fixed, paraffin-
embedded tissue can be stored for several years x High numbers of experiments
per biopsy are possible
x Fresh biopsies must be fixed or snap-frozen directly, in order to preserve epitopes
x Non-specific binding of primary and secondary antibodies, need for proper controls
x Testing and titration of all new antibodies x Low number of markers analyzed simultaneously
x Low sensitivity (enzyme conjugated antibodies can be amplified via indirect detection to increase sensitivity)
x No general consensus on what is “positive stain”
x Variation of staining intensity caused by the staining method or by the fixation procedure
x Susceptible to photobleaching: exposure to light may diminish fluorescent signals over time
x Ability to assess hundreds of tissue samples on a single microscope slide x Identical experimental
x Same as for IHC
x Several cores from each tumor necessary to ensure valid representation of heterogeneous tumors
x Both quantitative and qualitative analysis x Reproducible
interquantification x Rapid analysis of thousands
x Quantification of multiple parameters (<40) (Advantage compared with IHC/IF) x Detection of low-level
x No information of microanatomical localization x Fresh samples needed
x Dependent on sufficient cell numbers
x Sensitive process of preparation of high-quality single-cell suspensions, especially for solid tissues. Fragile cell types might be under-
x Protocols must be individually designed for different tissues and cells of interest
x Biased technique based on predetermined markers x Number of markers limited (compared with scRNAseq) x Markers does not exist in all colours
x Stained samples are susceptible to photobleaching